ArticleJournal of the American Medical Informatics Association : JAMIA2024
Improving reporting standards for phenotyping algorithm in biomedical research: 5 fundamental dimensions.
Article in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- From study design to executable code: automating target trial emulation with large language models.JAMIA open · 2026Article
- Evaluating the feasibility of the CIPHER metadata framework towards building a conceptual phenotype standard.JAMIA open · 2026Article
- Cardiovascular-Kidney-Metabolic Syndrome: Development of anJMIR diabetes · 2026Article
- Exploring beyond diagnoses in electronic health records to improve discovery: a review of the phenome-wide association study.JAMIA open · 2025Review
- Validation of large language models for detecting pathologic complete response in breast cancer using population-based pathology reports.BMC medical informatics and decision making · 2024Article
- Variation in Phenotype Definitions in Observational Clinical Research: A Review of Three Conditions.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Review
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Authors and funding
6 authors.
Funding
Abstract
introductionPhenotyping algorithms enable the interpretation of complex health data and definition of clinically relevant phenotypes; they have become crucial in biomedical research. However, the lack of standardization and transparency inhibits the cross-comparison of findings among different studies, limits large scale meta-analyses, confuses the research community, and prevents the reuse of algorithms, which results in duplication of efforts and the waste of valuable resources. RECOMMENDATIONS: Here, we propose five independent fundamental dimensions of phenotyping algorithms-complexity, performance, efficiency, implementability, and maintenance-through which researchers can describe, measure, and deploy any algorithms efficiently and effectively. These dimensions must be considered in the context of explicit use cases and transparent methods to ensure that they do not reflect unexpected biases or exacerbate inequities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.